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Apple - Sr ML Infrastructure Engineer Siri User Experience Metrics Data United States, West Virginia 928051933
04.09.2025
As a Senior ML infrastructure Engineer on the Siri User Experience Metrics team, you will have significant influence and responsibility in shaping the architecture and scalability of our end-to-end machine learning infrastructure. You will lead initiatives to streamline model development workflows, ensure reliable deployment of ML models to production, and optimize performance across compute and storage.
We’re looking for an engineer to lead the design, development, and scaling of our machine learning infrastructure. This role is ideal for someone who thrives at the intersection of systems engineering and applied machine learning. You’ll be responsible for building robust, scalable, and maintainable infrastructure to support the full ML lifecycle - from data ingestion and feature computation to training, deployment, and monitoring in production.You’ll play a critical role in:- Designing and maintaining high-throughput, low-latency pipelines for real-time and batch inference.- Automating the model training and evaluation workflows with reproducibility and traceability in mind.- Defining infrastructure standards and best practices for ML experimentation, CI/CD, and observability.- Collaborating with ML researchers and engineers to improve productivity through tooling and platform enhancements.
- 7 years of development experience and Bachelors or Masters degree in Computer Science or 5 years development experience and PhD in Computer science or related field, with at least 3 years focused on large-scale machine learning infrastructure
- Proficient in Python with solid knowledge of software design principles.
- Expertise in designing and implementing distributed systems or data pipelines (e.g., Spark, Flink, Kafka, Airflow) and knowledge of SQL to analyze data and derive insights.
- Experience with ML lifecycle tools (e.g., MLflow, Metaflow, Kubeflow, SageMaker, Vertex AI).
- Hands-on experience with container orchestration and cloud-native services (e.g., Kubernetes, Docker, AWS/GCP/Azure).
- Leadership experience, including being a technical lead for complex, cross functional development projects demonstrating good technical judgement and prioritization skills. Strong communication skills and a proactive, ownership-driven mindset.
- Prior experience architecting ML platforms or Feature Stores in a fast-paced production environment.
- Experience with real-time model serving and streaming pipelines (e.g., Kafka, Flink, Ray Serve, Triton).
- Experience optimizing GPU and CPU resource allocation for training and inference workloads.
- Experience with any ML authoring framework (PyTorch, TensorFlow, JAX, etc.), particularly on-device ML frameworks such as CoreML, TFLite or ExecuTorch.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
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